126 lines
5.0 KiB
Python
126 lines
5.0 KiB
Python
import torch._functorch.apis as apis
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import torch._functorch.eager_transforms as _impl
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import torch._functorch.make_functional as _nn_impl
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from torch._functorch.vmap import in_dims_t, out_dims_t
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from torch._functorch.eager_transforms import argnums_t
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import torch.nn as nn
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import textwrap
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from typing import Any, Callable, Optional, Tuple, Union
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import warnings
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"""
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The APIs in this file are exposed as `functorch.*`. They are thin wrappers
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around the torch.func.* APIs that have deprecation warnings -- we're trying
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to move people to the torch.func.* equivalents.
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NB: We don't use *args, **kwargs in the signatures because that changes the
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documentation.
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"""
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def get_warning(api, new_api=None, replace_newlines=False):
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if new_api is None:
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new_api = f'torch.func.{api}'
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warning = (
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f"We've integrated functorch into PyTorch. As the final step of the \n"
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f"integration, functorch.{api} is deprecated as of PyTorch \n"
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f"2.0 and will be deleted in a future version of PyTorch >= 2.3. \n"
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f"Please use {new_api} instead; see the PyTorch 2.0 release notes \n"
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f"and/or the torch.func migration guide for more details \n"
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f"https://pytorch.org/docs/master/func.migrating.html"
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)
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if replace_newlines:
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warning = warning.replace("\n", "")
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return warning
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def warn_deprecated(api, new_api=None):
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warning = get_warning(api, new_api, replace_newlines=True)
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warnings.warn(warning, stacklevel=2)
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def setup_docs(functorch_api, torch_func_api=None, new_api_name=None):
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api_name = functorch_api.__name__
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if torch_func_api is None:
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torch_func_api = getattr(_impl, api_name)
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# See https://docs.python.org/3/using/cmdline.html#cmdoption-OO
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if torch_func_api.__doc__ is None:
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return
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warning = get_warning(api_name, new_api_name)
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warning_note = "\n.. warning::\n\n" + textwrap.indent(warning, " ")
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warning_note = textwrap.indent(warning_note, " ")
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functorch_api.__doc__ = torch_func_api.__doc__ + warning_note
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def vmap(
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func: Callable,
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in_dims: in_dims_t = 0,
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out_dims: out_dims_t = 0,
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randomness: str = 'error',
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*,
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chunk_size=None) -> Callable:
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warn_deprecated('vmap', 'torch.vmap')
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return apis.vmap(func, in_dims, out_dims, randomness, chunk_size=chunk_size)
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def grad(func: Callable, argnums: argnums_t = 0, has_aux: bool = False) -> Callable:
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warn_deprecated('grad')
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return apis.grad(func, argnums, has_aux)
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def grad_and_value(func: Callable, argnums: argnums_t = 0, has_aux: bool = False) -> Callable:
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warn_deprecated('grad_and_value')
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return apis.grad_and_value(func, argnums, has_aux)
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def vjp(func: Callable, *primals, has_aux: bool = False):
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warn_deprecated('vjp')
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return _impl.vjp(func, *primals, has_aux=has_aux)
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def jvp(func: Callable, primals: Any, tangents: Any, *, strict: bool = False, has_aux: bool = False):
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warn_deprecated('jvp')
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return _impl.jvp(func, primals, tangents, strict=strict, has_aux=has_aux)
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def jacrev(func: Callable, argnums: Union[int, Tuple[int]] = 0, *, has_aux=False,
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chunk_size: Optional[int] = None,
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_preallocate_and_copy=False):
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warn_deprecated('jacrev')
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return _impl.jacrev(func, argnums, has_aux=has_aux, chunk_size=chunk_size,
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_preallocate_and_copy=_preallocate_and_copy)
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def jacfwd(func: Callable, argnums: argnums_t = 0, has_aux: bool = False, *, randomness: str = "error"):
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warn_deprecated('jacfwd')
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return _impl.jacfwd(func, argnums, has_aux, randomness=randomness)
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def hessian(func, argnums=0):
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warn_deprecated('hessian')
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return _impl.hessian(func, argnums=argnums)
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def functionalize(func: Callable, *, remove: str = 'mutations') -> Callable:
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warn_deprecated('functionalize')
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return _impl.functionalize(func, remove=remove)
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def make_functional(model: nn.Module, disable_autograd_tracking: bool = False):
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warn_deprecated('make_functional', 'torch.func.functional_call')
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return _nn_impl.make_functional(model, disable_autograd_tracking)
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def make_functional_with_buffers(model: nn.Module, disable_autograd_tracking: bool = False):
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warn_deprecated('make_functional_with_buffers', 'torch.func.functional_call')
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return _nn_impl.make_functional_with_buffers(model, disable_autograd_tracking)
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def combine_state_for_ensemble(models):
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warn_deprecated('combine_state_for_ensemble', 'torch.func.stack_module_state')
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return _nn_impl.combine_state_for_ensemble(models)
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setup_docs(vmap, apis.vmap, 'torch.vmap')
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setup_docs(grad, apis.grad)
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setup_docs(grad_and_value, apis.grad_and_value)
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setup_docs(vjp)
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setup_docs(jvp)
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setup_docs(jacrev)
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setup_docs(jacfwd)
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setup_docs(hessian)
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setup_docs(functionalize)
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setup_docs(make_functional, _nn_impl.make_functional,
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'torch.func.functional_call')
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setup_docs(make_functional_with_buffers, _nn_impl.make_functional,
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'torch.func.functional_call')
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setup_docs(combine_state_for_ensemble, _nn_impl.combine_state_for_ensemble,
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'torch.func.stack_module_state')
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